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ICML
2004
IEEE
16 years 4 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 4 months ago
Multi-focal learning and its application to customer service support
In this study, we formalize a multi-focal learning problem, where training data are partitioned into several different focal groups and the prediction model will be learned within...
Yong Ge, Hui Xiong, Wenjun Zhou, Ramendra K. Sahoo...
136
Voted
ICML
2007
IEEE
16 years 4 months ago
Learning to combine distances for complex representations
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
ICML
2006
IEEE
16 years 4 months ago
Feature subset selection bias for classification learning
Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
Surendra K. Singhi, Huan Liu
133
Voted
GIS
2009
ACM
15 years 8 months ago
Machine learning approach to report prioritization with an application to travel time dissemination
This paper looks at the problem of data prioritization, commonly found in mobile ad-hoc networks. The proposed general solution uses a machine learning approach in order to learn ...
Piotr Szczurek, Bo Xu, Jie Lin, Ouri Wolfson